This disclosure relates to methods of detecting the presence and the identity of microorganisms in a sample.
Emergence of drug resistant pathogens is a global healthcare crisis that is forcing physicians to treat common infectious diseases with ever more potent antibiotics. This is largely caused by the complexity and time required in identifying the offending bacteria, forcing physicians to prescribe empirically even with the knowledge of the high negativity rate amongst cultured specimens. The net result has been a significant increase in emergence of resistant strains, higher treatment costs, and longer recovery cycle due to an increase in side effect risks associated with taking broad spectrum and unnecessary antibiotics.
Broad spectrum antibiotics are commonly prescribed when treating patients that are exhibiting symptoms of sepsis or septic shock. Given the seriousness of these conditions, doctors will often prescribe one or more broad-spectrum antibiotics right away and are not likely to change the treatment regimen until the full effect of the drugs can be assessed or results from microbiology become available. For instance, the document “Surviving Sepsis Campaign Guideline” (SSCG) recommends a treatment protocol in which intravenous antibiotics, consisting of one or more broad-spectrum agents against likely bacterial/fungal pathogens, should be started within the first hour of recognizing severe sepsis and septic shock [R. P. Dellinger et al., Crit. Care Med 2008]. The treatment protocol states that the antimicrobial regimen is to be reassessed daily, and once the pathogen is known, as a matter of good practice, a more appropriate narrow-spectrum antimicrobial drug is to be administered.
Unfortunately, current clinical bacteriology methods typically provide pathogen identification information when it may be too late to impact patient outcomes. This is due to the time lag of 2-3 days from specimen collection to reporting results of pathogen identification and susceptibility testing. Causes for the time lag include the need to transport specimens to clinical laboratories staffed by expert clinical bacteriologists and the time required for blood culture and subsequent colony formation after plating the specimen on solid culture medium. Specimens that arrive at the clinical microbiology laboratory after normal business hours are typically held overnight until staff arrives the next day. Once specimens are plated on solid agar on day 2 (after a positive blood culture has been obtained), an additional 8-12 hours are needed for colonies to form. Plates are examined, colonies are enumerated, and appropriate colonies are selected for identification and susceptibility testing. The process further requires analysis and interpretation before reports are released, typically on day 3, which may be too slow to meaningfully impact antibiotic selection and patient outcomes.
While many aspects of clinical microbiology laboratory workflow have been automated, clinical bacteriology remains highly labour-intensive. Many laboratories currently automate identification and susceptibility testing using either the Vitek (Biomerieux) or Phoenix (Becton-Dickenson) instruments. However, these systems, and newer systems based on mass spectroscopy, depend on selection of appropriate colonies from overnight growth on agar plates by expert personnel.
Several nucleic acid amplification approaches for clinical bacteriology have recently been commercialized. However, most of these still require an nucleic acid extraction and purification step that can take more than 1 hour, as part of the pre-analytical process for species identification. These processes are required for providing an inhibitor and contaminant free sample for nucleic acid assays. Consequently, despite their specificity and sensitivity, molecular methods such as PCR have not replaced the much slower standard microbial culture-based techniques as the front line test in the clinical microbiology laboratory, and the results from clinical microbiology testing continue to be provided too late to substantially impact patient outcomes.